Thermal state estimation of fused deposition modeling in additive manufacturing processes using Kalman filters

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Abstract
Summary: In this paper, a data assimilation method using a linear Kalman filter is presented to monitor the thermal state of a part during a fused deposition modeling process. The system model is found by discretizing the heat equation with the finite difference method. Infrared (IR) camera measurements are then combined with the system model via a linear Kalman filter. As a result of the data assimilation, the accuracy of monitoring the thermal field is improved, which is important for the qualification of bonding strength between layers. Furthermore, using the linear Kalman filter can allow for closed‐loop monitoring system because an IR camera can be guided to a location where the uncertainty of estimation is high. The closed‐loop monitoring system will be employed as a feedback system for adaptive control of system parameters during printing processes for the improvement of part quality.

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